Skip to main content
Glama

Insider Signal

insider_signal

Analyzes insider trading activity for stocks to classify purchase types, identify cluster buying patterns, and provide clear signal strength assessments with plain-English explanations.

Instructions

Interpret insider trading activity for any stock. Classifies open-market purchases vs. routine sales/awards, identifies cluster buying, and explains whether the activity is a meaningful signal. Returns signal strength (strong_buy → strong_sell) and a plain-English verdict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock ticker symbol (e.g. NVDA, AAPL, MSFT)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and succeeds by disclosing the classification logic (open-market vs routine), detection heuristics (cluster buying), and return format (strong_buy → strong_sell scale plus plain-English verdict). Missing only operational constraints like rate limits or data freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Every sentence earns its place: front-loaded purpose ('Interpret insider trading activity'), followed by processing logic ('Classifies... identifies... explains'), and concludes with return value specification. Zero redundancy in two dense sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description fully compensates by detailing the return structure (signal strength scale and verdict format) and explaining the analytical methodology applied to the input, making it complete for a single-parameter analysis tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with the 'ticker' parameter fully documented including examples (NVDA, AAPL, MSFT). The description adds no explicit parameter semantics, but baseline 3 is appropriate given the schema already provides complete documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description uses specific verb 'Interpret' with resource 'insider trading activity' and clearly distinguishes from siblings like 'stock_thesis' or 'earnings_analysis' by emphasizing unique capabilities: classifying open-market purchases vs routine sales, identifying cluster buying, and providing signal strength ratings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

While the specific focus on insider trading implies appropriate usage context, the description lacks explicit guidance on when to select this tool over siblings like 'bear_vs_bull' or 'valuation_snapshot', and does not mention prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/marras0914/agent-toolbelt'

If you have feedback or need assistance with the MCP directory API, please join our Discord server